Exemplary embodiments relate generally to production systems, and more particularly, to methods, systems and computer program products for optimizing production system throughput.
Throughput analysis for a production system can be very complex. The complexity of the analysis may be due to a complex process line layout, and/or to randomness in the process (including station breakdowns, random processing time, and the random number of parts produced by the system). Production throughput analysis is important for design, operation and management of production systems.
One key characteristic of any process performance is variability, due to the fact that a process rarely performs consistently over time. The bottleneck of a production line is the machine, or station, that most severely impedes the system performance. Bottlenecks are one of the main causes of system variability and fluctuation in production. Methods such as statistical bottleneck analysis (utilized to determine a long-term system bottleneck) cannot correctly identify short-term system bottlenecks. The reason is twofold: first, for short time periods, random events may not follow any distribution pattern; and second, initial conditions (e.g., initial buffer levels) are not important for long-term statistical bottleneck analysis while they are key parameters in short-term bottleneck analysis.
Short-term production analysis and short-term bottleneck identification are important to allowing manufacturing operations to respond optimally to dynamic changes in system behavior. Plant production monitoring systems can provide real time production information. Production supervisors use output from the system to make real time decisions, such as deciding initial and end buffer status and dispatch maintenance skill trades. However, the decisions are up to each individual's experience, and some times the decisions may be far from optimal. Currently, there is no systematic method, backed up by real-time decision support tools to help production supervisors effectively control and optimize plant operations on a day-to-day basis. A real-time supervisory control and on-line optimization method is needed to mitigate short-term production system constraints (e.g., bottlenecks) to improve system throughput.